Mechanical and durability properties of concretes containing recycled lime powder and recycled aggregates

According to a recent report by the European Commission, within the European Union, the construction and demolition wastes come to at least 450 million tons per year. Roughly 75% of the waste is disposed to landfill, despite its major recycling potential. The bulk constituents of demolition debris are concrete (50-55%) and masonry (30-40%) with only small percentages of other materials such as metals, glass and timber. In Cyprus, at present, recycling of waste materials is practically inexistent and almost the entire demolition waste products are disposed in landfill sites, with all possible economic, technical and environmental impacts. This research paper presents the evaluation and the effective reuse of waste construction materials, such as recycled lime powder (RLP) and recycled concrete aggregates (RCA), disposed to landfill sites in Cyprus, due to the lack of a lucid recycling policy and knowledge. Results show that both RLP and RCA have the potential to produce good quality and robust concrete mixtures both in terms of mechanical and durability performance. © 2013 Elsevier B.V. All rights reserved.

Design, construction and evaluation of systems to predict risk in obstetrics.

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

Articulated wooden blades for a horizontal-axis wind turbine. Design, construction and testing.

A pair of blades were constructed following a Tapered Chord, Zero Twist pattern after Anderson. The construction uses the Wood Epoxy Saturation Technique, with a solid Beech main spar and leading edge joined together with laminated veneers of beech forming a D-section; the trailing edge is formed from millimetre ply skins, foam filled to resist compressive loads. This construction leads to an extremely light, flexible blade, with the centres of gravity and torsion well forward, giving good stability. Each blade has three built-in strain gauges, alowing flapwise bending to be measured. Stiffness, and natural frequencies, were measured, to input to a numerical computer model to calculate blade deformation during operation, and to determine stability boundaries of the blade. Preliminary aerodynamic performance measurements are presented and close agreement is found with theory.

Content Based Integration of Construction Site Images in Architecture, Engineering, Construction, and Facilities Management (AEC/FM) Model based Systems

This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

Zero carbon manufacturing facility - Towards integrating material, energy, and waste process flows

The increasing pressure on material availability, energy prices, as well as emerging environmental legislation is leading manufacturers to adopt solutions to reduce their material and energy consumption as well as their carbon footprint, thereby becoming more sustainable. Ultimately manufacturers could potentially become zero carbon by having zero net energy demand and zero waste across the supply chain. The literature on zero carbon manufacturing and the technologies that underpin it are growing, but there is little available on how a manufacturer undertakes the transition. Additionally, the work in this area is fragmented and clustered around technologies rather than around processes that link the technologies together. There is a need to better understand material, energy, and waste process flows in a manufacturing facility from a holistic viewpoint. With knowledge of the potential flows, design methodologies can be developed to enable zero carbon manufacturing facility creation. This paper explores the challenges faced when attempting to design a zero carbon manufacturing facility. A broad scope is adopted from legislation to technology and from low waste to consuming waste. A generic material, energy, and waste flow model is developed and presented to show the material, energy, and waste inputs and outputs for the manufacturing system and the supporting facility and, importantly, how they can potentially interact. Finally the application of the flow model in industrial applications is demonstrated to select appropriate technologies and configure them in an integrated way. © 2009 IMechE.

Mechanical and leaching behaviour of slag-cement and lime-activated slag stabilised/solidified contaminated soil.

Stabilisation/solidification (S/S) is an effective technique for reducing the leachability of contaminants in soils. Very few studies have investigated the use of ground granulated blast furnace slag (GGBS) for S/S treatment of contaminated soils, although it has been shown to be effective in ground improvement. This study sought to investigate the potential of GGBS activated by cement and lime for S/S treatment of a mixed contaminated soil. A sandy soil spiked with 3000mg/kg each of a cocktail of heavy metals (Cd, Ni, Zn, Cu and Pb) and 10,000mg/kg of diesel was treated with binder blends of one part hydrated lime to four parts GGBS (lime-slag), and one part cement to nine parts GGBS (slag-cement). Three binder dosages, 5, 10 and 20% (m/m) were used and contaminated soil-cement samples were compacted to their optimum water contents. The effectiveness of the treatment was assessed using unconfined compressive strength (UCS), permeability and acid neutralisation capacity (ANC) tests with determination of contaminant leachability at the different acid additions. UCS values of up to 800kPa were recorded at 28days. The lowest coefficient of permeability recorded was 5×10(-9)m/s. With up to 20% binder dosage, the leachability of the contaminants was reduced to meet relevant environmental quality standards and landfill waste acceptance criteria. The pH-dependent leachability of the metals decreased over time. The results show that GGBS activated by cement and lime would be effective in reducing the leachability of contaminants in contaminated soils.

Near-complete transuranic waste incineration in a thorium fuelled pressurised water reactor

The production of long-lived transuranic (TRU) waste is a major disadvantage of fission-based nuclear power. Incineration, and virtual elimination, of waste stockpiles is possible in a thorium (Th) fuelled critical or subcritical fast reactor. Fuel cycles producing a net decrease in TRUs are possible in conventional pressurised water reactors (PWRs). However, minor actinides (MAs) have a detrimental effect on reactivity and stability, ultimately limiting the quality and quantity of waste that can be incinerated. In this paper, we propose using a thorium-retained-actinides fuel cycle in PWRs, where the reactor is fuelled with a mixture of thorium and TRU waste, and after discharge all actinides are reprocessed and returned to the reactor. To investigate the feasibility and performance of this fuel cycle an assembly-level analysis for a one-batch reloading strategy was completed over 125 years of operation using WIMS 9. This one-batch analysis was performed for simplicity, but allowed an indicative assessment of the performance of a four-batch fuel management strategy. The build-up of 233U in the reactor allowed continued reactive and stable operation, until all significant actinide populations had reached pseudo-equilibrium in the reactor. It was therefore possible to achieve near-complete transuranic waste incineration, even for fuels with significant MA content. The average incineration rate was initially around 330 kg per GW th year and tended towards 250 kg per GW th year over several decades: a performance comparable to that achieved in a fast reactor. Using multiple batch fuel management, competitive or improved end-of-cycle burn-up appears achievable. The void coefficient (VC), moderator temperature coefficient (MTC) and Doppler coefficient remained negative. The quantity of soluble boron required for a fixed fuel cycle length was comparable to that for enriched uranium fuel, and acceptable amounts can be added without causing a positive VC or MTC. This analysis is limited by the consideration of a single fuel assembly, and it will be necessary to perform a full core coupled neutronic-thermal-hydraulic analysis to determine if the design in its current form is feasible. In particular, the potential for positive VCs if the core is highly or locally voided is a cause for concern. However, these results provide a compelling case for further work on concept feasibility and fuel management, which is in progress. © 2011 Elsevier Ltd. All rights reserved.